-------------------------------------------------------------------------------
       log:  C:\wip\inequality\replicationdata2\SSreplication.log
  log type:  text
 opened on:   4 Oct 2008, 16:28:00

. /*********************
> * Table 1
> **********************/
> 
> use "OECD 1996 wage data.dta", clear;

. xi: reg top10_top1 i.state;
i.state           _Istate_1-11        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =     170
-------------+------------------------------           F(  9,   160) =  183.57
       Model |  1633.06509     9  181.451677           Prob > F      =  0.0000
    Residual |   158.15675   160  .988479686           R-squared     =  0.9117
-------------+------------------------------           Adj R-squared =  0.9067
       Total |  1791.22184   169  10.5989458           Root MSE      =  .99422

------------------------------------------------------------------------------
  top10_top1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   7.305095   .3410157    21.42   0.000     6.631623    7.978568
   _Istate_3 |   2.728108   .3410157     8.00   0.000     2.054635     3.40158
   _Istate_4 |   6.720868   .3410157    19.71   0.000     6.047395     7.39434
   _Istate_5 |    3.25545   .3410157     9.55   0.000     2.581977    3.928922
   _Istate_6 |  (dropped)
   _Istate_7 |   1.512595   .3410157     4.44   0.000     .8391226    2.186068
   _Istate_8 |   1.757395   .3410157     5.15   0.000     1.083922    2.430867
   _Istate_9 |   .8401194   .3410157     2.46   0.015     .1666469    1.513592
  _Istate_10 |  -3.127882   .3410157    -9.17   0.000    -3.801354   -2.454409
  _Istate_11 |   6.071597   .3410157    17.80   0.000     5.398124    6.745069
       _cons |   22.64455   .2411345    93.91   0.000     22.16833    23.12076
------------------------------------------------------------------------------

. predict etop10_top1 if e(sample), res;
(17 missing values generated)

. xi: reg _90_10 i.state;
i.state           _Istate_1-11        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =     137
-------------+------------------------------           F( 10,   126) =  167.02
       Model |  42.3235371    10  4.23235371           Prob > F      =  0.0000
    Residual |  3.19295964   126   .02534095           R-squared     =  0.9299
-------------+------------------------------           Adj R-squared =  0.9243
       Total |  45.5164968   136  .334680123           Root MSE      =  .15919

------------------------------------------------------------------------------
      _90_10 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   1.404754   .0682515    20.58   0.000     1.269686    1.539821
   _Istate_3 |  -.3056134   .0615984    -4.96   0.000    -.4275149   -.1837119
   _Istate_4 |   .2923412   .0546012     5.35   0.000      .184287    .4003953
   _Istate_5 |   .3767411   .0554478     6.79   0.000     .2670117    .4864706
   _Istate_6 |   .2532537   .0554478     4.57   0.000     .1435243    .3629832
   _Istate_7 |  -.2676589   .0634408    -4.22   0.000    -.3932065   -.1421114
   _Istate_8 |   .1306412   .0755919     1.73   0.086     -.018953    .2802353
   _Istate_9 |  -.1453388   .0809866    -1.79   0.075     -.305609    .0149313
  _Istate_10 |  -.7790088   .0574518   -13.56   0.000    -.8927043   -.6653133
  _Istate_11 |   .9788647   .0546012    17.93   0.000     .8708106    1.086919
       _cons |   2.839659   .0386089    73.55   0.000     2.763253    2.916065
------------------------------------------------------------------------------

. predict e90_10 if e(sample), res;
(50 missing values generated)

. xi: reg _90_50 i.state;
i.state           _Istate_1-11        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =     137
-------------+------------------------------           F( 10,   126) =   81.35
       Model |  2.04985395    10  .204985395           Prob > F      =  0.0000
    Residual |  .317505461   126  .002519885           R-squared     =  0.8659
-------------+------------------------------           Adj R-squared =  0.8552
       Total |  2.36735941   136  .017407054           Root MSE      =   .0502

------------------------------------------------------------------------------
      _90_50 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   .1315441   .0215224     6.11   0.000     .0889519    .1741363
   _Istate_3 |  -.0692514   .0194244    -3.57   0.001    -.1076918    -.030811
   _Istate_4 |   .0864706   .0172179     5.02   0.000     .0523968    .1205444
   _Istate_5 |   .2565441   .0174849    14.67   0.000      .221942    .2911462
   _Istate_6 |   .1196691   .0174849     6.84   0.000      .085067    .1542712
   _Istate_7 |  -.0507059   .0200054    -2.53   0.012    -.0902961   -.0111158
   _Istate_8 |   .0102941   .0238371     0.43   0.667    -.0368789    .0574671
   _Istate_9 |  -.0207059   .0255383    -0.81   0.419    -.0712455    .0298337
  _Istate_10 |  -.1504202   .0181169    -8.30   0.000    -.1862729   -.1145675
  _Istate_11 |        .19   .0172179    11.04   0.000     .1559262    .2240738
       _cons |   1.704706   .0121749   140.02   0.000     1.680612      1.7288
------------------------------------------------------------------------------

. predict e90_50 if e(sample), res;
(50 missing values generated)

. xi: reg _50_10 i.state if e(sample);
i.state           _Istate_1-11        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =     137
-------------+------------------------------           F( 10,   126) =  318.28
       Model |  7.23095611    10  .723095611           Prob > F      =  0.0000
    Residual |  .286260135   126  .002271906           R-squared     =  0.9619
-------------+------------------------------           Adj R-squared =  0.9589
       Total |  7.51721625   136  .055273649           Root MSE      =  .04766

------------------------------------------------------------------------------
      _50_10 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   .6453677    .020436    31.58   0.000     .6049255    .6858099
   _Istate_3 |  -.1167914   .0184439    -6.33   0.000    -.1532914   -.0802914
   _Istate_4 |   .0811765   .0163488     4.97   0.000     .0488227    .1135303
   _Istate_5 |  -.0258823   .0166023    -1.56   0.122    -.0587378    .0069731
   _Istate_6 |   .0297427   .0166023     1.79   0.076    -.0031127    .0625981
   _Istate_7 |  -.1108824   .0189956    -5.84   0.000    -.1484741   -.0732907
   _Istate_8 |   .0657843   .0226339     2.91   0.004     .0209926    .1105761
   _Istate_9 |  -.0658823   .0242492    -2.72   0.008    -.1138707   -.0178939
  _Istate_10 |   -.340168   .0172023   -19.77   0.000     -.374211   -.3061251
  _Istate_11 |   .3458824   .0163488    21.16   0.000     .3135286    .3782361
       _cons |   1.665882   .0115603   144.10   0.000     1.643005     1.68876
------------------------------------------------------------------------------

. predict e50_10 if e(sample) , res;
(50 missing values generated)

. pwcorr top10_top1 _90_10 _90_50 _50_10, obs;

             | top10_~1   _90_10   _90_50   _50_10
-------------+------------------------------------
  top10_top1 |   1.0000 
             |      170
             |
      _90_10 |   0.8180   1.0000 
             |      121      137
             |
      _90_50 |   0.7173   0.8127   1.0000 
             |      121      137      137
             |
      _50_10 |   0.7688   0.9556   0.6100   1.0000 
             |      121      137      137      137
             |

. pwcorr etop10_top1 e90_10 e90_50 e50_10, obs;

             | etop10~1   e90_10   e90_50   e50_10
-------------+------------------------------------
 etop10_top1 |   1.0000 
             |      170
             |
      e90_10 |   0.6281   1.0000 
             |      121      137
             |
      e90_50 |   0.7892   0.8854   1.0000 
             |      121      137      137
             |
      e50_10 |   0.3202   0.8652   0.5415   1.0000 
             |      121      137      137      137
             |

. use "lydall replication.dta", clear;

. xi: reg top10_top1 i.state;
i.state           _Istate_1-12        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =      39
-------------+------------------------------           F(  9,    29) =    5.39
       Model |  335.864842     9  37.3183158           Prob > F      =  0.0002
    Residual |  200.724995    29  6.92155157           R-squared     =  0.6259
-------------+------------------------------           Adj R-squared =  0.5098
       Total |  536.589838    38  14.1207852           Root MSE      =  2.6309

------------------------------------------------------------------------------
  top10_top1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |    10.0668   1.921326     5.24   0.000     6.137243    13.99635
   _Istate_3 |   .6394094   2.201156     0.29   0.774    -3.862459    5.141278
   _Istate_4 |   1.667325   1.764851     0.94   0.353      -1.9422     5.27685
   _Istate_5 |  (dropped)
   _Istate_6 |   4.812409   1.499835     3.21   0.003     1.744903    7.879916
   _Istate_7 |    12.0569   2.881989     4.18   0.000     6.162574    17.95123
   _Istate_8 |  (dropped)
   _Istate_9 |   3.909232   1.764851     2.22   0.035     .2997065    7.518757
  _Istate_10 |    6.18535   1.663917     3.72   0.001     2.782258    9.588443
  _Istate_11 |   3.120228   1.764851     1.77   0.088    -.4892969    6.729753
  _Istate_12 |   5.347805   1.921326     2.78   0.009     1.418252    9.277359
       _cons |   23.19046   1.176567    19.71   0.000     20.78411    25.59681
------------------------------------------------------------------------------

. predict etop10_top1 if e(sample), res;
(15 missing values generated)

. xi: reg _90_15 i.state;
i.state           _Istate_1-12        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =      54
-------------+------------------------------           F( 11,    42) =    5.65
       Model |  68.4982432    11  6.22711302           Prob > F      =  0.0000
    Residual |  46.2819768    42  1.10195183           R-squared     =  0.5968
-------------+------------------------------           Adj R-squared =  0.4912
       Total |   114.78022    53  2.16566453           Root MSE      =  1.0497

------------------------------------------------------------------------------
      _90_15 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   3.310115   .7041863     4.70   0.000      1.88901    4.731221
   _Istate_3 |    .941087   .7666209     1.23   0.226    -.6060167    2.488191
   _Istate_4 |  -.1715644   .7041863    -0.24   0.809     -1.59267    1.249541
   _Istate_5 |   .0529871   1.149931     0.05   0.963    -2.267668    2.373643
   _Istate_6 |  -.1797421   .5984433    -0.30   0.765    -1.387449    1.027965
   _Istate_7 |  -.0225985   .7041863    -0.03   0.975    -1.443704    1.398507
   _Istate_8 |   1.365948   .5855164     2.33   0.025     .1843279    2.547568
   _Istate_9 |   1.470129   .7041863     2.09   0.043     .0490235    2.891234
  _Istate_10 |   .9036263   .6639132     1.36   0.181    -.4362047    2.243457
  _Istate_11 |   2.121191   .7041863     3.01   0.004      .700086    3.542297
  _Istate_12 |   3.103632   .7666209     4.05   0.000     1.556529    4.650736
       _cons |   3.385609   .4694575     7.21   0.000     2.438206    4.333013
------------------------------------------------------------------------------

. predict e90_15 if e(sample), res;

. xi: reg _90_50 i.state;
i.state           _Istate_1-12        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =      54
-------------+------------------------------           F( 11,    42) =    7.29
       Model |  2.92115967    11   .26555997           Prob > F      =  0.0000
    Residual |  1.53001606    42  .036428954           R-squared     =  0.6563
-------------+------------------------------           Adj R-squared =  0.5662
       Total |  4.45117574    53  .083984448           Root MSE      =  .19086

------------------------------------------------------------------------------
      _90_50 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |      .5445   .1280353     4.25   0.000     .2861144    .8028856
   _Istate_3 |   .1386666   .1393871     0.99   0.326     -.142628    .4199613
   _Istate_4 |      .1145   .1280353     0.89   0.376    -.1438856    .3728856
   _Istate_5 |       .342   .2090807     1.64   0.109    -.0799419     .763942
   _Istate_6 |      .3595   .1088091     3.30   0.002     .1399144    .5790855
   _Istate_7 |      .1305   .1280353     1.02   0.314    -.1278857    .3888856
   _Istate_8 |   .7242222   .1064587     6.80   0.000     .5093799    .9390646
   _Istate_9 |      .1995   .1280353     1.56   0.127    -.0588856    .4578856
  _Istate_10 |       .134   .1207128     1.11   0.273    -.1096083    .3776083
  _Istate_11 |      .4045   .1280353     3.16   0.003     .1461144    .6628856
  _Istate_12 |   .4586667   .1393871     3.29   0.002     .1773721    .7399613
       _cons |      1.618   .0853568    18.96   0.000     1.445743    1.790257
------------------------------------------------------------------------------

. predict e90_50 if e(sample), res;

. xi: reg _50_15 i.state if e(sample);
i.state           _Istate_1-12        (_Istate_1 for state==AUS omitted)

      Source |       SS       df       MS              Number of obs =      54
-------------+------------------------------           F( 11,    42) =    9.26
       Model |   11.705779    11  1.06416172           Prob > F      =  0.0000
    Residual |  4.82657704    42  .114918501           R-squared     =  0.7081
-------------+------------------------------           Adj R-squared =  0.6316
       Total |   16.532356    53  .311931246           Root MSE      =    .339

------------------------------------------------------------------------------
      _50_15 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   _Istate_2 |   .9813894   .2274056     4.32   0.000     .5224663    1.440313
   _Istate_3 |   .3582971   .2475679     1.45   0.155    -.1413151    .8579094
   _Istate_4 |   -.234534   .2274056    -1.03   0.308    -.6934571    .2243892
   _Istate_5 |  -.3341748   .3713519    -0.90   0.373    -1.083593    .4152436
   _Istate_6 |  -.4681118   .1932576    -2.42   0.020    -.8581215   -.0781021
   _Istate_7 |    -.16767   .2274056    -0.74   0.465    -.6265932    .2912531
   _Istate_8 |  -.0598093   .1890831    -0.32   0.753    -.4413944    .3217759
   _Istate_9 |   .5832228   .2274056     2.56   0.014     .1242997    1.042146
  _Istate_10 |    .279227   .2144001     1.30   0.200    -.1534499    .7119039
  _Istate_11 |   .5824119   .2274056     2.56   0.014     .1234887    1.041335
  _Istate_12 |   1.050769   .2475679     4.24   0.000     .5511568    1.550381
       _cons |   2.088561   .1516038    13.78   0.000     1.782612     2.39451
------------------------------------------------------------------------------

. predict e50_15 if e(sample) , res;

. pwcorr top10_top1 _90_15 _90_50 _50_15, obs;

             | top10_~1   _90_15   _90_50   _50_15
-------------+------------------------------------
  top10_top1 |   1.0000 
             |       39
             |
      _90_15 |   0.4665   1.0000 
             |       39       54
             |
      _90_50 |   0.6539   0.6362   1.0000 
             |       39       54       54
             |
      _50_15 |   0.2857   0.8959   0.2407   1.0000 
             |       39       54       54       54
             |

. pwcorr etop10_top1 e90_15 e90_50 e50_15, obs;

             | etop10~1   e90_15   e90_50   e50_15
-------------+------------------------------------
 etop10_top1 |   1.0000 
             |       39
             |
      e90_15 |   0.4636   1.0000 
             |       39       54
             |
      e90_50 |   0.6787   0.8181   1.0000 
             |       39       54       54
             |
      e50_15 |   0.2094   0.9066   0.5193   1.0000 
             |       39       54       54       54
             |

. clear;

. /*********************
> * Table 2
> **********************/
> 
> miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart p3-p18, nsets(10)
> ;
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |  .53681 .0716395     7.493        142    0.000
  mgdppc |   .01867      .055678      0.335        112    0.738
tradedep |   .01884     .0089159      2.113         81    0.038
secsharel10 |  .44228   1.231137      0.359         93    0.720
wdeccentld |  1.1348    .4565763      2.485         48    0.016
 wcentld |   .09987      .492732      0.203         78    0.840
 totden2 |  -.05766     .0146771     -3.928         68    0.000
 leftgov |   .25186     .3938983      0.639         48    0.526
  nondem |   1.2906     .8184767      1.577         29    0.126
 funisuf |   1.2574     .3921027      3.207        290    0.001
 fempart |  -14.822     5.885693     -2.518         24    0.019
      p3 |  -.03784     .7428633     -0.051         11    0.960
      p4 |   .23303     .4217888      0.552         18    0.587
      p5 |   .90763     .5515926      1.645         13    0.124
      p6 |  -.47703     .5785099     -0.825         12    0.425
      p7 |  -1.4111     .6028657     -2.341         16    0.033
      p8 |  -.69222     .7494665     -0.924         14    0.372
      p9 |  -1.1414     .6350889     -1.797         20    0.087
     p10 |  -.44233     .7381705     -0.599         21    0.555
     p11 |  -.36754     .7487096     -0.491         24    0.628
     p12 |  -.79101     .9267167     -0.854         20    0.403
     p13 |  -.94757     1.080887     -0.877         21    0.391
     p14 |    -1.28     1.139309     -1.124         23    0.273
     p15 |  -.52051     1.237955     -0.420         24    0.678
     p16 |  -.47691     1.261534     -0.378         26    0.708
     p17 |  -.24768     1.279828     -0.194         30    0.848
     p18 |  -.43604     1.449279     -0.301         27    0.766
   _cons |   16.742     2.911676      5.750         68    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart c2-c13 p3-p18, ns
> ets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |  .38919 .0706564     5.508        421    0.000
  mgdppc |   .00539     .0810502      0.067        294    0.947
tradedep |   .02623     .0142968      1.835         57    0.072
secsharel10 | -1.4619   1.409076     -1.037        177    0.301
wdeccentld |  1.3141    .4382849      2.998        141    0.003
 wcentld |   .30019      .499215      0.601        181    0.548
 totden2 |  -.07063     .0188109     -3.755         73    0.000
 leftgov |  -.34564     .3628548     -0.953         75    0.344
  nondem |    1.582      .866561      1.826         22    0.081
 funisuf |   1.2981     .4605916      2.818        152    0.005
 fempart |  -11.481     5.117856     -2.243         35    0.031
      c2 |   1.1684     .7361993      1.587         68    0.117
      c3 |   .44953     .8000852      0.562        139    0.575
      c4 |  -1.2735     1.256062     -1.014        114    0.313
      c5 |  -1.2481     1.073422     -1.163         94    0.248
      c6 |  -.80778     .5705627     -1.416        157    0.159
      c7 |  -1.9154     .7899028     -2.425        146    0.017
      c8 |  -1.1315     .9341285     -1.211        128    0.228
      c9 |  -1.6822     .8845792     -1.902        118    0.060
     c10 |  -.30991     1.085484     -0.286        175    0.776
     c11 |   -1.133     .7437593     -1.523        309    0.129
     c12 |    -.818     .8259503     -0.990        397    0.323
     c13 |  -.25595     .8625481     -0.297        137    0.767
      p3 |  -.17796     .6588533     -0.270         11    0.792
      p4 |   .15474     .4319225      0.358         17    0.724
      p5 |   .94796     .4908506      1.931         14    0.073
      p6 |  -.26168     .5041915     -0.519         15    0.611
      p7 |  -1.1955     .5495163     -2.175         22    0.040
      p8 |  -.50974     .7301351     -0.698         18    0.494
      p9 |   -1.156     .7370485     -1.568         22    0.131
     p10 |  -.55533     .8027751     -0.692         27    0.495
     p11 |  -.45106     .8388904     -0.538         32    0.595
     p12 |  -.73662     1.034215     -0.712         27    0.482
     p13 |  -.73412      1.24812     -0.588         27    0.561
     p14 |  -1.0862     1.342767     -0.809         32    0.425
     p15 |  -.36796     1.444758     -0.255         36    0.800
     p16 |  -.14993     1.546747     -0.097         38    0.923
     p17 |   .05206     1.626706      0.032         42    0.975
     p18 |   .04207     1.828652      0.023         43    0.982
   _cons |   21.394     2.721603      7.861        206    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart p3-p18, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .55617     .0714057      7.789         73    0.000
  mgdppc |   .08871     .0685864      1.293         78    0.200
tradedep |   .02231     .0111354      2.004         74    0.049
secsharel10 | -.30586   1.408256     -0.217         79    0.829
wdeccentld |  1.5535    .5670274      2.740         39    0.009
 wcentld |   .02055     .6802543      0.030         41    0.976
 totden2 |  -.06445     .0208964     -3.084         45    0.003
 leftgov |  -.09754     .5205219     -0.187         37    0.852
  nondem |   2.2709     .9367178      2.424         34    0.021
 funisuf |   .95349     .4753918      2.006        131    0.047
 fempart |  -21.087      7.53867     -2.797         22    0.011
      p3 |  -.89706     .9477196     -0.947         10    0.366
      p4 |  -.25833     .5379726     -0.480         16    0.638
      p5 |  -.31039     .6763098     -0.459         13    0.654
      p6 |  -1.2063     .5573389     -2.164         17    0.045
      p7 |  -3.3088     .6908266     -4.790         17    0.000
      p8 |  -2.1379     .9252048     -2.311         14    0.036
      p9 |  -2.5725     .7536788     -3.413         27    0.002
     p10 |  -2.0686     .8304609     -2.491         36    0.017
     p11 |  -1.8405     .8563608     -2.149         46    0.037
     p12 |  -2.5441     1.103777     -2.305         27    0.029
     p13 |  -2.8118     1.318979     -2.132         26    0.043
     p14 |  -3.6229     1.387675     -2.611         28    0.014
     p15 |  -2.6162     1.513747     -1.728         32    0.093
     p16 |  -1.9372     1.559698     -1.242         34    0.223
     p17 |  -1.8833     1.581866     -1.191         38    0.241
     p18 |  -1.7578     1.850177     -0.950         29    0.350
   _cons |   22.647     4.082371      5.547         38    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart c2-c13 p3-p18, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .46758     .0717719      6.515         94    0.000
  mgdppc |   .09762      .105874      0.922        191    0.358
tradedep |   .02389     .0183701      1.301         43    0.200
secsharel10 |  -2.095   1.647851     -1.271        165    0.205
wdeccentld |  1.6219    .5592319      2.900         73    0.005
 wcentld |   .07913     .7070786      0.112         82    0.911
 totden2 |  -.07771     .0266785     -2.913         38    0.006
 leftgov |  -.67307      .490159     -1.373         44    0.177
  nondem |   2.5417     .9906991      2.566         32    0.015
 funisuf |   .58955     .5739078      1.027        127    0.306
 fempart |  -17.734     7.423087     -2.389         23    0.025
      c2 |   1.3206     .8472567      1.559         69    0.124
      c3 |   1.0774     .9947457      1.083        105    0.281
      c4 |  -.41786      1.61331     -0.259        111    0.796
      c5 |  -.78868      1.40917     -0.560        101    0.577
      c6 |  -.90403     .8138162     -1.111        180    0.268
      c7 |  -1.7799     .9943144     -1.790        182    0.075
      c8 |  -.89415     1.248279     -0.716         94    0.476
      c9 |  -.80801     1.160119     -0.696        121    0.487
     c10 |  -.14157     1.364351     -0.104        138    0.918
     c11 |  -1.1753      .928678     -1.266        422    0.206
     c12 |  -.57804     1.010527     -0.572        259    0.568
     c13 |  -.14315     1.127849     -0.127         95    0.899
      p3 |  -.84822     .9093544     -0.933         11    0.372
      p4 |  -.22024     .5491129     -0.401         16    0.694
      p5 |  -.15914     .6478036     -0.246         13    0.810
      p6 |  -1.0389     .5185471     -2.003         19    0.059
      p7 |  -3.0863     .6867796     -4.494         21    0.000
      p8 |  -1.8824     .9159754     -2.055         17    0.056
      p9 |  -2.5482     .8726156     -2.920         24    0.008
     p10 |  -2.1533     .8709704     -2.472         45    0.017
     p11 |  -1.9689     .9452121     -2.083         52    0.042
     p12 |  -2.5542     1.244133     -2.053         30    0.049
     p13 |  -2.6638     1.555518     -1.712         27    0.098
     p14 |  -3.4901      1.69864     -2.055         30    0.049
     p15 |  -2.5582     1.872343     -1.366         32    0.181
     p16 |  -1.8421     2.000292     -0.921         36    0.363
     p17 |  -1.7441     2.140269     -0.815         35    0.421
     p18 |  -1.4798     2.495783     -0.593         31    0.558
   _cons |   26.489     4.183621      6.332         42    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart p3-p18, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .57822     .0691448      8.362         45    0.000
  mgdppc |   .10269     .0450935      2.277        180    0.024
tradedep |   .00814      .006648      1.225         66    0.225
secsharel10 | -.89856   .9017871     -0.996         77    0.322
wdeccentld |  .77765    .3578869      2.173         46    0.035
 wcentld |  -.10771      .463868     -0.232         36    0.818
 totden2 |  -.01675     .0119603     -1.400         42    0.169
 leftgov |  -.44527      .312067     -1.427         60    0.159
  nondem |    1.615     .5936367      2.721         48    0.009
 funisuf |  -.20044     .3238432     -0.619         65    0.538
 fempart |  -11.266     4.896487     -2.301         20    0.032
      p3 |  -1.3167     .5657944     -2.327         10    0.041
      p4 |  -.65962     .3689688     -1.788         13    0.096
      p5 |  -1.5545      .416683     -3.731         13    0.003
      p6 |  -1.0949     .2723602     -4.020         49    0.000
      p7 |  -2.9822     .5186593     -5.750         15    0.000
      p8 |  -2.2261     .5608402     -3.969         16    0.001
      p9 |  -2.2259     .5744676     -3.875         21    0.001
     p10 |  -2.4106     .5079041     -4.746         55    0.000
     p11 |   -2.198     .5908147     -3.720         44    0.001
     p12 |  -2.6133     .7202209     -3.628         32    0.001
     p13 |  -2.7764     .8267108     -3.358         34    0.002
     p14 |  -3.4222     .8506611     -4.023         45    0.000
     p15 |  -3.0404     .9378185     -3.242         47    0.002
     p16 |  -2.1288     .9933249     -2.143         54    0.037
     p17 |  -2.3888     1.019914     -2.342         55    0.023
     p18 |  -1.9436     1.185251     -1.640         43    0.108
   _cons |   9.3121     2.012968      4.626         21    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart c2-c13 p3-p18, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 219
Number of Groups: 13
Obs per group: max = 17
Obs per group: avg = 16.84615384615385
Obs per group: min = 15
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .53913     .0762533      7.070         36    0.000
  mgdppc |   .13865     .0759977      1.824        198    0.070
tradedep |   .00265     .0123494      0.215         30    0.831
secsharel10 | -1.0899   1.074483     -1.014        122    0.312
wdeccentld |  .73221    .4106193      1.783         50    0.081
 wcentld |  -.21663     .4859771     -0.446         53    0.658
 totden2 |  -.02113     .0173353     -1.219         32    0.232
 leftgov |  -.53174     .3178219     -1.673         52    0.100
  nondem |   1.6383     .6569856      2.494         49    0.016
 funisuf |  -.62965     .4183864     -1.505         70    0.137
 fempart |   -10.55     5.622492     -1.876         17    0.078
      c2 |   .56002     .5946299      0.942         85    0.349
      c3 |   .87774     .6963301      1.261        154    0.209
      c4 |   .90144     1.115009      0.808        115    0.420
      c5 |   .40823     .9355328      0.436        116    0.663
      c6 |  -.19862     .6129663     -0.324        242    0.746
      c7 |  -.38972     .6314305     -0.617        177    0.538
      c8 |   .13905     .9158523      0.152        115    0.880
      c9 |   .68103     .8588504      0.793        175    0.429
     c10 |   .18221     .9206894      0.198         90    0.844
     c11 |  -.23967     .6760063     -0.355        902    0.723
     c12 |   .11447     .6778442      0.169        117    0.866
     c13 |   .22676     .7734535      0.293         69    0.770
      p3 |  -1.1924     .5838301     -2.042         11    0.067
      p4 |  -.59508     .3820237     -1.558         14    0.142
      p5 |  -1.4465     .4409896     -3.280         12    0.006
      p6 |  -1.0535     .2763358     -3.812         43    0.000
      p7 |  -2.9353     .5425188     -5.411         16    0.000
      p8 |  -2.1445     .6022139     -3.561         16    0.003
      p9 |  -2.2278     .6075588     -3.667         21    0.001
     p10 |  -2.4946     .5418077     -4.604         60    0.000
     p11 |  -2.3619         .635     -3.720         58    0.000
     p12 |   -2.795     .8233406     -3.395         37    0.002
     p13 |   -2.957     1.004965     -2.942         35    0.006
     p14 |  -3.6168     1.093374     -3.308         43    0.002
     p15 |  -3.3041     1.248999     -2.645         40    0.012
     p16 |  -2.4955     1.338519     -1.864         53    0.068
     p17 |  -2.7159     1.469374     -1.848         43    0.071
     p18 |  -2.2954     1.741287     -1.318         36    0.196
   _cons |   9.8801     2.520528      3.920         20    0.001
---------------------------------------------------------------


. /*********************
> * Table 3
> **********************/
> 
> miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart p15-p18 if period
> >15, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |  .70785 .0991892     7.136        206    0.000
  mgdppc |  -.02763     .0708346     -0.390        415    0.697
tradedep |   .01411      .009507      1.484        138    0.140
secsharel10 | -.04752   1.947637     -0.024        219    0.981
wdeccentld |  1.5382    .4576808      3.361       1107    0.001
 wcentld |   .43419     .7815943      0.556         47    0.581
 totden2 |  -.03254     .0185609     -1.753        116    0.082
 leftgov |   .46025     .4949927      0.930        252    0.353
  nondem |        0            0          .          .        .
 funisuf |   12.591     13.88645      0.907         32    0.371
 fempart |  -7.5263     7.633028     -0.986         32    0.332
     p15 |   .88811     .3944291      2.252         17    0.038
     p16 |   .81781     .3590409      2.278         21    0.033
     p17 |   1.0941     .3987057      2.744         47    0.009
     p18 |    .9062     .5919988      1.531         66    0.131
   _cons |  -2.7123     14.38785     -0.189         34    0.852
---------------------------------------------------------------


. miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart c2-c13 p15-p18 if
>  period>15, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |   .1906 .1464368     1.302        651    0.194
  mgdppc |   .19248       .14348      1.342        117    0.182
tradedep |    .0273     .0216812      1.259         32    0.217
secsharel10 | -.47238   2.879443     -0.164         96    0.870
wdeccentld |   1.253    .6210979      2.017        250    0.045
 wcentld |   .34831     .7538123      0.462         85    0.645
 totden2 |  -.04944     .0282532     -1.750        186    0.082
 leftgov |  -.08342     .4350521     -0.192        203    0.848
  nondem |        0            0          .          .        .
 funisuf |   16.794     10.99208      1.528         25    0.139
 fempart |  -2.8289     5.813429     -0.487         41    0.629
      c2 |   1.7408     1.361447      1.279         51    0.207
      c3 |   1.9969     1.455025      1.372         92    0.173
      c4 |  -.19458     2.820799     -0.069         36    0.945
      c5 |  -3.0113     1.889014     -1.594         50    0.117
      c6 |  -1.0948     1.210896     -0.904        249    0.367
      c7 |  -3.5991      1.23837     -2.906        130    0.004
      c8 |   1.4102     2.349005      0.600         97    0.550
      c9 |  -.85495     1.598982     -0.535        121    0.594
     c10 |  -3.2386     2.056173     -1.575         78    0.119
     c11 |  -1.9805     1.229977     -1.610        547    0.108
     c12 |   -2.209     1.401232     -1.576        345    0.116
     c13 |  -1.0395     1.580621     -0.658        118    0.512
     p15 |   .15601     .3508378      0.445         50    0.658
     p16 |    .0425       .59697      0.071        183    0.943
     p17 |   .13447     .9475503      0.142         75    0.888
     p18 |  -.21589     1.425716     -0.151         88    0.880
   _cons |   3.1207     14.13002      0.221         34    0.827
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart p15-p18 if period>15, nsets(1
> 0);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .81405     .0956676      8.509        205    0.000
  mgdppc |   .04027      .080656      0.499        215    0.618
tradedep |   .01049     .0129827      0.808        204    0.420
secsharel10 | -1.1175   2.468373     -0.453        206    0.651
wdeccentld |  2.1446    .6475565      3.312        853    0.001
 wcentld |   .26355     1.051808      0.251         44    0.803
 totden2 |  -.01828     .0244626     -0.747        119    0.456
 leftgov |   .34138     .6323466      0.540        202    0.590
  nondem |        0            0          .          .        .
 funisuf |   20.486     17.94495      1.142         26    0.264
 fempart |  -9.5372     10.01964     -0.952         35    0.348
     p15 |   1.3979     .4791752      2.917         19    0.009
     p16 |   1.8789     .4613951      4.072         20    0.001
     p17 |   1.9219     .4814537      3.992         41    0.000
     p18 |   1.9718     .7229364      2.728         39    0.010
   _cons |  -12.941     18.48508     -0.700         33    0.489
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart c2-c13 p15-p18 if period>15, 
> nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .34127     .1442537      2.366        504    0.018
  mgdppc |   .36488      .181234      2.013         82    0.047
tradedep |   .02776     .0328874      0.844         36    0.404
secsharel10 |  .75476   3.711287      0.203         95    0.839
wdeccentld |  2.1787    .7731139      2.818        194    0.005
 wcentld |   .40619     1.030378      0.394        103    0.694
 totden2 |  -.06046     .0449636     -1.345        117    0.181
 leftgov |  -.00493     .6103369     -0.008        183    0.994
  nondem |        0            0          .          .        .
 funisuf |   15.661     15.64357      1.001         20    0.329
 fempart |  -5.6759     8.730002     -0.650         34    0.520
      c2 |   1.0634     1.671418      0.636         41    0.528
      c3 |   2.3018     1.819158      1.265         62    0.210
      c4 |   1.0192     3.726539      0.274         45    0.786
      c5 |  -2.7073     2.304933     -1.175         64    0.244
      c6 |  -.74058     1.534944     -0.482        280    0.630
      c7 |  -2.9845     1.493891     -1.998        124    0.048
      c8 |   2.8952     3.028887      0.956        132    0.341
      c9 |   1.4552     2.038369      0.714        151    0.476
     c10 |  -2.6919     2.851058     -0.944         67    0.348
     c11 |  -2.6191     1.648741     -1.589        632    0.113
     c12 |  -1.8008     1.996721     -0.902        347    0.368
     c13 |  -.13282     2.147889     -0.062        107    0.951
     p15 |   .00468     .5556824      0.008         44    0.993
     p16 |   .04648     .9370444      0.050         98    0.961
     p17 |   -.1519     1.437051     -0.106         70    0.916
     p18 |  -.61107     2.156711     -0.283         79    0.778
   _cons |   1.2484     18.85822      0.066         31    0.948
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart p15-p18 if period>15, nsets(10)
> ;
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .90243     .0741709     12.167        324    0.000
  mgdppc |   .08948     .0457335      1.956         39    0.058
tradedep |  -.00114     .0073662     -0.155        260    0.877
secsharel10 | -1.5997   1.291729     -1.238         59    0.220
wdeccentld |  1.4048    .4550678      3.087        326    0.002
 wcentld |  -.05987     .5727656     -0.105         43    0.917
 totden2 |   .01179     .0103926      1.134         61    0.261
 leftgov |  -.06226     .3330262     -0.187         87    0.852
  nondem |        0            0          .          .        .
 funisuf |   14.227     9.953354      1.429         13    0.176
 fempart |  -4.9291     6.151976     -0.801         21    0.432
     p15 |   .67509     .2632277      2.565         15    0.021
     p16 |   1.6063     .2237352      7.179         25    0.000
     p17 |   1.2098     .2652323      4.561         30    0.000
     p18 |   1.6042     .3991247      4.019         24    0.000
   _cons |  -13.702     10.18759     -1.345         15    0.199
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart c2-c13 p15-p18 if period>15, ns
> ets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 65
Number of Groups: 13
Obs per group: max = 5
Obs per group: avg = 5
Obs per group: min = 5
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .78864     .1639606      4.810         99    0.000
  mgdppc |   .21674     .1342399      1.615         58    0.112
tradedep |    .0062     .0255756      0.242         37    0.810
secsharel10 | -.16881   2.188197     -0.077         84    0.939
wdeccentld |  1.0882    .5499184      1.979         81    0.051
 wcentld |  -.21794     .6677519     -0.326         33    0.746
 totden2 |  -.01019     .0307902     -0.331         98    0.741
 leftgov |   -.1365      .317936     -0.429         60    0.669
  nondem |        0            0          .          .        .
 funisuf |   9.9657     12.62267      0.790         15    0.442
 fempart |  -2.5649      6.63343     -0.387         18    0.704
      c2 |   -.1964     .9919482     -0.198         33    0.844
      c3 |   .75848     1.158013      0.655         43    0.516
      c4 |   .95354     2.524404      0.378         37    0.708
      c5 |   -.4884     1.550012     -0.315         54    0.754
      c6 |  -.07575     .9491307     -0.080        180    0.936
      c7 |  -1.0671     .9582768     -1.114        104    0.268
      c8 |   1.0323     1.932623      0.534        121    0.594
      c9 |   .67074     1.331034      0.504         76    0.616
     c10 |   .23111     1.907984      0.121         52    0.904
     c11 |  -.80296     .8989647     -0.893        153    0.373
     c12 |   .21049     1.320527      0.159         96    0.874
     c13 |    .7658     1.488395      0.515         66    0.609
     p15 |   .24987     .4221448      0.592         74    0.556
     p16 |   .78183     .7136417      1.096         85    0.276
     p17 |   .20147     1.039304      0.194         93    0.847
     p18 |   .20003     1.558121      0.128         86    0.898
   _cons |  -11.362     13.59503     -0.836         21    0.413
---------------------------------------------------------------


. /*********************
> * Table 4
> **********************/
> 
> miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart p3-p13 if period<
> =15, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |  .43724 .0936714     4.668        284    0.000
  mgdppc |   .04296     .0847166      0.507        197    0.613
tradedep |   .01443     .0173972      0.830         60    0.410
secsharel10 |  .18992   1.427593      0.133        296    0.894
wdeccentld |   .8675    .5602128      1.549         42    0.129
 wcentld |   .30861     .6974873      0.442         92    0.659
 totden2 |  -.08731     .0226896     -3.848         96    0.000
 leftgov |   .37976     .4998139      0.760         73    0.450
  nondem |   1.1984     .8589594      1.395         47    0.169
 funisuf |   1.6184     .5032414      3.216        870    0.001
 fempart |  -16.798     7.603722     -2.209         26    0.036
      p3 |   -.1809     .7187956     -0.252         12    0.806
      p4 |  -.00559     .4750649     -0.012         23    0.991
      p5 |   .64218      .568725      1.129         16    0.276
      p6 |   -.5814     .6062842     -0.959         14    0.353
      p7 |  -1.4538     .6471601     -2.246         20    0.036
      p8 |  -.88889     .7731081     -1.150         17    0.266
      p9 |   -1.424     .7856805     -1.812         22    0.083
     p10 |  -.89406     .8803722     -1.016         28    0.318
     p11 |  -.86666     .9464204     -0.916         30    0.367
     p12 |  -1.3213     1.184082     -1.116         25    0.275
     p13 |  -1.5312     1.379914     -1.110         27    0.277
   _cons |   21.314     3.826068      5.571         89    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la_top1la top10_top1laL1 mgdppc tradedep secsharel10
>   wdeccentld wcentld totden leftgov nondem funisuf  fempart c2-c13 p3-p13 if 
> period<=15, nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la_top1la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10_top1laL1 |   .2604 .0925499     2.814        791    0.005
  mgdppc |   .03745     .1393081      0.269         76    0.789
tradedep |    .0195     .0255623      0.763         33    0.451
secsharel10 | -.79081   1.899134     -0.416        142    0.678
wdeccentld |  .90672    .5871454      1.544        155    0.125
 wcentld |   .75884      .670795      1.131        178    0.259
 totden2 |  -.09759     .0268991     -3.628         98    0.000
 leftgov |  -.30954     .4697219     -0.659         66    0.512
  nondem |   1.0347     .9371441      1.104         33    0.277
 funisuf |   1.0816     .6120957      1.767        209    0.079
 fempart |  -11.389     6.539859     -1.742         41    0.089
      c2 |   2.1395     .9798356      2.184         72    0.032
      c3 |   .19892     1.170337      0.170         79    0.865
      c4 |  -.47476     1.566703     -0.303         91    0.763
      c5 |   .21904     1.447909      0.151         67    0.880
      c6 |   .11053     .7296319      0.151         80    0.880
      c7 |  -1.8334     1.096341     -1.672        106    0.097
      c8 |  -.50526     1.192531     -0.424         91    0.673
      c9 |  -1.4639     1.166713     -1.255        118    0.212
     c10 |   .52768     1.476936      0.357        137    0.721
     c11 |  -.15887     1.064274     -0.149        140    0.882
     c12 |  -.11196     1.236121     -0.091        199    0.928
     c13 |   .80823     1.162426      0.695        102    0.488
      p3 |  -.21358     .6544267     -0.326         13    0.749
      p4 |   .06356     .5167574      0.123         22    0.903
      p5 |   .83749     .5254892      1.594         21    0.126
      p6 |  -.21611     .6067971     -0.356         20    0.725
      p7 |  -1.1604     .7224304     -1.606         35    0.117
      p8 |  -.75749     .9206114     -0.823         27    0.418
      p9 |  -1.6306     1.121766     -1.454         25    0.158
     p10 |  -1.3221     1.243817     -1.063         29    0.296
     p11 |  -1.2819      1.36412     -0.940         31    0.355
     p12 |   -1.653     1.680745     -0.984         28    0.334
     p13 |  -1.7666     2.022672     -0.873         28    0.390
   _cons |   25.839     3.283147      7.870       2609    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart p3-p13 if period<=15, nsets(1
> 0);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .42318     .0869455      4.867        120    0.000
  mgdppc |   .02901     .0969715      0.299         87    0.766
tradedep |   .03139     .0211371      1.485         52    0.144
secsharel10 | -.15743   1.537533     -0.102        385    0.919
wdeccentld |  .98653    .6699573      1.473         34    0.150
 wcentld |   .30744     .8938296      0.344         41    0.733
 totden2 |  -.11148     .0282746     -3.943         63    0.000
 leftgov |   .14578     .5847002      0.249         59    0.804
  nondem |   2.1299     .9085022      2.344         84    0.021
 funisuf |    .9491     .5815413      1.632        281    0.104
 fempart |  -21.909     8.898962     -2.462         25    0.021
      p3 |   -.9792     .9160756     -1.069         11    0.309
      p4 |  -.56681      .599071     -0.946         16    0.358
      p5 |  -.70325     .6417749     -1.096         15    0.290
      p6 |  -1.3893     .5591258     -2.485         20    0.022
      p7 |  -3.2909     .7112331     -4.627         21    0.000
      p8 |  -2.4809     .8932701     -2.777         17    0.013
      p9 |  -3.0891     .8989737     -3.436         25    0.002
     p10 |  -2.7807     .9164566     -3.034         44    0.004
     p11 |  -2.5601      1.01459     -2.523         41    0.016
     p12 |  -3.2058     1.318046     -2.432         26    0.022
     p13 |  -3.5352     1.532979     -2.306         28    0.029
   _cons |   30.036     4.980716      6.030         50    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top10la top10laL1 mgdppc tradedep secsharel10  wdeccentld
>  wcentld totden leftgov nondem funisuf  fempart c2-c13 p3-p13 if period<=15, 
> nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top10la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top10laL1 |  .29663     .0845043      3.510        274    0.001
  mgdppc |   .05933      .173439      0.342         69    0.733
tradedep |   .03282     .0323987      1.013         26    0.320
secsharel10 | -1.4746   2.048442     -0.720        263    0.472
wdeccentld |  .72234    .7339456      0.984         96    0.327
 wcentld |   .49394     .9723884      0.508         79    0.613
 totden2 |  -.11904     .0346365     -3.437         67    0.001
 leftgov |  -.49408     .6138045     -0.805         42    0.425
  nondem |   1.7027     1.032993      1.648         62    0.104
 funisuf |  -.19177     .6924695     -0.277        620    0.782
 fempart |    -16.9     8.415342     -2.008         32    0.053
      c2 |   2.6862     .9187584      2.924        131    0.004
      c3 |   .64121     1.379101      0.465         87    0.643
      c4 |   .25649     1.806484      0.142         88    0.887
      c5 |   .94352      1.77342      0.532         61    0.597
      c6 |   .03985     .9398107      0.042         87    0.966
      c7 |  -2.0965     1.308629     -1.602         72    0.114
      c8 |  -.04753     1.448933     -0.033         79    0.974
      c9 |  -.55134     1.362018     -0.405        136    0.686
     c10 |   .34721     1.663811      0.209        176    0.835
     c11 |   .22104     1.184635      0.187        145    0.852
     c12 |   .34352     1.343542      0.256        283    0.798
     c13 |   .44716     1.437598      0.311         73    0.757
      p3 |  -.75466     .8827256     -0.855         11    0.410
      p4 |  -.33444     .6296103     -0.531         20    0.601
      p5 |  -.36154     .6562403     -0.551         19    0.588
      p6 |  -1.0526     .6585573     -1.598         26    0.122
      p7 |   -2.937     .8443926     -3.478         37    0.001
      p8 |  -2.3501     1.087078     -2.162         27    0.040
      p9 |  -3.3878     1.315345     -2.576         27    0.016
     p10 |   -3.315     1.370716     -2.418         40    0.020
     p11 |  -3.1744     1.556828     -2.039         40    0.048
     p12 |   -3.735     1.969584     -1.896         31    0.067
     p13 |  -3.9739     2.406564     -1.651         29    0.109
   _cons |   34.607     4.642193      7.455        103    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart p3-p13 if period<=15, nsets(10)
> ;
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .45251     .0832469      5.436         64    0.000
  mgdppc |  -.00732     .0708507     -0.103        245    0.918
tradedep |   .02539     .0118737      2.138         75    0.036
secsharel10 | -.40265   1.032518     -0.390        310    0.697
wdeccentld |  .31365    .4218625      0.743         53    0.460
 wcentld |  -.00526       .66424     -0.008         35    0.994
 totden2 |  -.04127     .0176533     -2.338         43    0.024
 leftgov |  -.34742     .3381362     -1.027        152    0.306
  nondem |   1.4781     .6751036      2.189         63    0.032
 funisuf |  -.69093     .4007824     -1.724        143    0.087
 fempart |  -9.8673     5.406317     -1.825         30    0.078
      p3 |  -1.2106     .5880371     -2.059         11    0.065
      p4 |  -.72945     .4095735     -1.781         14    0.096
      p5 |  -1.7024     .3983695     -4.273         15    0.001
      p6 |  -1.1938     .3133205     -3.810         50    0.000
      p7 |  -2.8517     .5612305     -5.081         18    0.000
      p8 |  -2.3324     .5872699     -3.972         18    0.001
      p9 |  -2.4611     .6775192     -3.633         22    0.001
     p10 |  -2.6558     .6226519     -4.265         52    0.000
     p11 |  -2.3916     .7322212     -3.266         42    0.002
     p12 |  -2.6864     .9225055     -2.912         32    0.007
     p13 |   -2.827     1.042786     -2.711         40    0.010
   _cons |   11.921     2.441838      4.882         27    0.000
---------------------------------------------------------------


. miest iqimpr xtpcse top1la top1laL1 mgdppc tradedep secsharel10  wdeccentld w
> centld totden leftgov nondem funisuf  fempart c2-c13 p3-p13 if period<=15, ns
> ets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Estimates

Model: Linear regression, correlated panels corrected standard errors (PCSEs)
Group Variable: stnum
Time Variable: period
Panels: correlated
Autocorrelation: independent
Dependent Variable: top1la

Number of Observations: 154
Number of Groups: 13
Obs per group: max = 12
Obs per group: avg = 11.84615384615385
Obs per group: min = 10
---------------------------------------------------------------
         |      Coef.   Std. Err.       t          Df     P>|t|
---------------------------------------------------------------
top1laL1 |   .36805     .0938518      3.922         54    0.000
  mgdppc |   .04741     .1247642      0.380        112    0.705
tradedep |   .02159     .0203217      1.062         23    0.299
secsharel10 | -.97149   1.602578     -0.606        117    0.546
wdeccentld | -.00285    .6147862     -0.005         47    0.996
 wcentld |  -.20378     .7384751     -0.276         44    0.784
 totden2 |  -.04386     .0256411     -1.711         33    0.097
 leftgov |  -.36868     .4142794     -0.890         62    0.377
  nondem |   1.1159     .7670191      1.455         65    0.151
 funisuf |  -1.4761     .5711856     -2.584        114    0.011
 fempart |  -9.6538     6.003145     -1.608         27    0.120
      c2 |    1.126     .7626038      1.477         86    0.143
      c3 |   .61337      .965758      0.635        128    0.526
      c4 |   .92683     1.235014      0.750         68    0.456
      c5 |   1.0236      1.21967      0.839         43    0.406
      c6 |  -.03264     .7121628     -0.046        137    0.964
      c7 |  -.75579     .7211396     -1.048         52    0.299
      c8 |   .51629     1.000469      0.516        105    0.607
      c9 |   .90665     .9799088      0.925        135    0.356
     c10 |    -.058     1.080962     -0.054         98    0.957
     c11 |   .50048     .8754872      0.572        280    0.568
     c12 |   .62819     .9433529      0.666         80    0.507
     c13 |  -.21973     1.002673     -0.219         45    0.828
      p3 |  -.96766     .6042346     -1.601         12    0.136
      p4 |  -.58597     .4143989     -1.414         20    0.173
      p5 |  -1.5383     .4575788     -3.362         16    0.004
      p6 |  -1.1309     .3428763     -3.298        105    0.001
      p7 |  -2.7321     .6195686     -4.410         28    0.000
      p8 |  -2.3602     .7150165     -3.301         23    0.003
      p9 |  -2.6598     .8245973     -3.226         32    0.003
     p10 |  -2.9591     .8751641     -3.381         53    0.001
     p11 |    -2.81     1.004504     -2.797         62    0.007
     p12 |  -3.1058     1.317306     -2.358         43    0.023
     p13 |  -3.2667     1.618232     -2.019         42    0.050
   _cons |   13.392     2.889189      4.635         28    0.000
---------------------------------------------------------------


. /*********************
> * Table 5
> **********************/
> 
> use "ineqlwdrep.dta", clear;

. tsset stnum year;
       panel variable:  stnum (unbalanced)
        time variable:  year, 1900 to 2000
                delta:  1 unit

. sort stnum year;

. /* Linearly interpolate missing L1.top1i values */  
> 
> qby stnum: ipolate top1la year, gen(top1i);

. qby stnum: ipolate top10la year, gen(top10i);

. gen top10_1x=100*((top10i-top1i)/(100-top1i));
(433 missing values generated)

. /*  Sweden Top Incomes*/ 
> 
> gen trend1=year-1900;

. gen trend2=year-1900;

. replace trend1=0 if year>1937;
(819 real changes made)

. replace trend2=0 if year<1938;
(460 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     41.33
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1009627   .0362835    -2.78   0.007    -.1729945   -.0289309
      trend2 |  -.1203234   .0160181    -7.51   0.000    -.1521233   -.0885236
       _cons |   31.32748   1.015047    30.86   0.000     29.31236     33.3426
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(819 real changes made)

. replace trend2=year-1900;
(460 real changes made)

. replace trend2=0 if year<1943;
(525 real changes made)

. replace trend1=0 if year>1942;
(754 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     44.86
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1051553   .0321743    -3.27   0.002    -.1690293   -.0412813
      trend2 |  -.1207543   .0163487    -7.39   0.000    -.1532107    -.088298
       _cons |   31.34471   1.080828    29.00   0.000     29.19899    33.49042
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(754 real changes made)

. replace trend2=year-1900;
(525 real changes made)

. replace trend2=0 if year<1948;
(590 real changes made)

. replace trend1=0 if year>1947;
(689 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     50.05
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0934148   .0278182    -3.36   0.001    -.1486408   -.0381887
      trend2 |   -.117937   .0159329    -7.40   0.000    -.1495678   -.0863061
       _cons |   31.06136   1.081125    28.73   0.000     28.91506    33.20767
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(689 real changes made)

. replace trend2=year-1900;
(590 real changes made)

. replace trend2=0 if year<1953;
(655 real changes made)

. replace trend1=0 if year>1952;
(624 real changes made)

.  newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     43.04
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1164684   .0291457    -4.00   0.000    -.1743299   -.0586069
      trend2 |  -.1230034   .0162218    -7.58   0.000    -.1552078    -.090799
       _cons |    31.5121   1.132654    27.82   0.000      29.2635     33.7607
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(624 real changes made)

. replace trend2=year-1900;
(655 real changes made)

. replace trend2=0 if year<1958;
(720 real changes made)

. replace trend1=0 if year>1957;
(559 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     39.55
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1289192   .0274062    -4.70   0.000    -.1833275   -.0745109
      trend2 |  -.1257571   .0159477    -7.89   0.000    -.1574174   -.0940968
       _cons |   31.79885   1.140555    27.88   0.000     29.53456    34.06313
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(559 real changes made)

. replace trend2=year-1900;
(720 real changes made)

. replace trend2=0 if year<1963;
(785 real changes made)

. replace trend1=0 if year>1962;
(494 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     39.98
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1204311   .0241472    -4.99   0.000    -.1683694   -.0724928
      trend2 |  -.1240148   .0151432    -8.19   0.000     -.154078   -.0939517
       _cons |   31.58457   1.089746    28.98   0.000     29.42115    33.74799
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(494 real changes made)

. replace trend2=year-1900;
(785 real changes made)

. replace trend2=0 if year<1968;
(850 real changes made)

. replace trend1=0 if year>1967;
(429 real changes made)

. newey top10_1x trend1 trend2 if state=="SWE" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        98
maximum lag: 5                                      F(  2,    95)  =     41.29
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1103015   .0216945    -5.08   0.000    -.1533705   -.0672324
      trend2 |  -.1225891    .014523    -8.44   0.000    -.1514208   -.0937573
       _cons |    31.2972   1.040621    30.08   0.000     29.23131     33.3631
------------------------------------------------------------------------------

.  /* Netherlands Top Incomes */ 
> 
> replace trend1=year-1900;
(429 real changes made)

. replace trend2=year-1900;
(850 real changes made)

. replace trend2=0 if year<1931;
(369 real changes made)

. replace trend1=0 if year>1930;
(910 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =     99.68
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |   -.168175    .050414    -3.34   0.001    -.2684465   -.0679036
      trend2 |  -.1450275   .0173966    -8.34   0.000    -.1796287   -.1104262
       _cons |   36.23132   1.163369    31.14   0.000     33.91742    38.54521
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(910 real changes made)

. replace trend2=year-1900;
(369 real changes made)

. replace trend2=0 if year<1936;
(434 real changes made)

. replace trend1=0 if year>1935;
(845 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =     97.48
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1573294   .0517734    -3.04   0.003    -.2603046   -.0543542
      trend2 |  -.1437596   .0191264    -7.52   0.000    -.1818013   -.1057179
       _cons |   36.14407   1.355865    26.66   0.000     33.44731    38.84083
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(845 real changes made)

. replace trend2=year-1900;
(434 real changes made)

. replace trend2=0 if year<1941;
(499 real changes made)

. replace trend1=0 if year>1940;
(780 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =    100.97
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |   -.130973   .0459147    -2.85   0.005    -.2222954   -.0396506
      trend2 |   -.137226   .0188061    -7.30   0.000    -.1746306   -.0998213
       _cons |   35.63687   1.400162    25.45   0.000       32.852    38.42173
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(780 real changes made)

. replace trend2=year-1900;
(499 real changes made)

. replace trend2=0 if year<1946;
(564 real changes made)

. replace trend1=0 if year>1945;
(715 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =    108.17
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0452319   .0303518    -1.49   0.140    -.1056003    .0151366
      trend2 |  -.1112278   .0139781    -7.96   0.000    -.1390297   -.0834259
       _cons |   33.49655   .9870158    33.94   0.000     31.53342    35.45969
------------------------------------------------------------------------------

. test trend1=trend2;

 ( 1)  trend1 - trend2 = 0

       F(  1,    83) =   12.09
            Prob > F =    0.0008

.  replace trend1=year-1900;
(715 real changes made)

. replace trend2=year-1900;
(564 real changes made)

. replace trend2=0 if year<1951;
(629 real changes made)

. replace trend1=0 if year>1950;
(650 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =     98.94
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0456974   .0322691    -1.42   0.160    -.1098794    .0184846
      trend2 |  -.1096539   .0148471    -7.39   0.000    -.1391841   -.0801237
       _cons |   33.25153   1.041574    31.92   0.000     31.17988    35.32318
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(650 real changes made)

. replace trend2=year-1900;
(629 real changes made)

. replace trend2=0 if year<1956;
(694 real changes made)

. replace trend1=0 if year>1955;
(585 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =     81.44
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0828704    .034149    -2.43   0.017    -.1507913   -.0149495
      trend2 |  -.1210502   .0145602    -8.31   0.000    -.1500098   -.0920906
       _cons |   34.13265   1.016554    33.58   0.000     32.11077    36.15454
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(585 real changes made)

. replace trend2=year-1900;
(694 real changes made)

. replace trend2=0 if year<1961;
(759 real changes made)

. replace trend1=0 if year>1960;
(520 real changes made)

. newey top10_1x trend1 trend2 if state=="NED" , lag(5);

Regression with Newey-West standard errors          Number of obs  =        86
maximum lag: 5                                      F(  2,    83)  =     81.62
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    top10_1x |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1170933   .0277925    -4.21   0.000    -.1723715   -.0618152
      trend2 |  -.1323145   .0124039   -10.67   0.000    -.1569853   -.1076437
       _cons |   35.10459   .8438445    41.60   0.000     33.42621    36.78296
------------------------------------------------------------------------------

.  /* Sweden Wages */
> 
> use "ljungbergseriesrep.dta", clear;

. tsset year;
        time variable:  year, 1900 to 2000
                delta:  1 unit

. gen trend1=year-1900;

. gen trend2=year-1900;

. replace trend1=0 if year>1937;
(63 real changes made)

. replace trend2=0 if year<1938;
(37 real changes made)

. newey multiple trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =     83.54
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0163428    .004613    -3.54   0.001    -.0254971   -.0071886
      trend2 |  -.0199285   .0017407   -11.45   0.000     -.023383   -.0164741
       _cons |   3.081313   .1246002    24.73   0.000     2.834048    3.328578
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(63 real changes made)

. replace trend2=year-1900;
(37 real changes made)

. replace trend2=0 if year<1943;
(42 real changes made)

. replace trend1=0 if year>1942;
(58 real changes made)

. newey multiple trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =     90.77
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0170038   .0040279    -4.22   0.000     -.024997   -.0090106
      trend2 |  -.0199835   .0018362   -10.88   0.000    -.0236273   -.0163397
       _cons |   3.082379   .1347669    22.87   0.000     2.814938    3.349819
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(58 real changes made)

. replace trend2=year-1900;
(42 real changes made)

. replace trend2=0 if year<1948;
(47 real changes made)

. replace trend1=0 if year>1947;
(53 real changes made)

. newey multiple trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =     99.62
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0184437   .0036333    -5.08   0.000    -.0256538   -.0112336
      trend2 |  -.0202318   .0018341   -11.03   0.000    -.0238715   -.0165922
       _cons |   3.101466    .137306    22.59   0.000     2.828987    3.373945
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(53 real changes made)

. replace trend2=year-1900;
(47 real changes made)

. replace trend2=0 if year<1953;
(52 real changes made)

. replace trend1=0 if year>1952;
(48 real changes made)

. newey multiple trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =     99.02
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0213373   .0032959    -6.47   0.000    -.0278779   -.0147967
      trend2 |  -.0207935   .0017415   -11.94   0.000    -.0242493   -.0173376
       _cons |   3.156939   .1314275    24.02   0.000     2.896125    3.417752
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(48 real changes made)

. replace trend2=year-1900;
(52 real changes made)

. replace trend2=0 if year<1958;
(57 real changes made)

. replace trend1=0 if year>1957;
(43 real changes made)

. newey multiple trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =    100.08
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0235156   .0029257    -8.04   0.000    -.0293215   -.0177097
      trend2 |  -.0211859   .0016571   -12.78   0.000    -.0244744   -.0178974
       _cons |   3.207269   .1272137    25.21   0.000     2.954818    3.459721
------------------------------------------------------------------------------

.   replace trend1=year-1900;
(43 real changes made)

. replace trend2=year-1900;
(57 real changes made)

. replace trend2=0 if year<1963;
(62 real changes made)

. replace trend1=0 if year>1962;
(38 real changes made)

. newey multiple trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =    103.99
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0228985   .0027052    -8.46   0.000    -.0282669     -.01753
      trend2 |  -.0210189   .0016223   -12.96   0.000    -.0242384   -.0177994
       _cons |   3.197134   .1276703    25.04   0.000     2.943776    3.450492
------------------------------------------------------------------------------

. replace trend1=year-1900;
(38 real changes made)

. replace trend2=year-1900;
(62 real changes made)

. replace trend2=0 if year<1968;
(67 real changes made)

. replace trend1=0 if year>1967;
(33 real changes made)

. newey multiple trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =       101
maximum lag: 5                                      F(  2,    98)  =    106.10
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
    multiple |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0217749   .0026301    -8.28   0.000    -.0269943   -.0165555
      trend2 |  -.0207929   .0015975   -13.02   0.000    -.0239631   -.0176227
       _cons |   3.171637   .1283828    24.70   0.000     2.916866    3.426409
------------------------------------------------------------------------------

.   /* Denmark Series */ 
> 
> use "denmarkintegerseriesrep.dta", clear;

. tsset year;
        time variable:  year, 1870 to 1965
                delta:  1 unit

. gen trend1=year-1900;

. gen trend2=year-1900;

. replace trend1=0 if year>1918;
(47 real changes made)

. replace trend2=0 if year<1919;
(48 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     70.33
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1832229   .0924994    -1.98   0.051    -.3669347    .0004888
      trend2 |  -.2082992   .0322286    -6.46   0.000     -.272308   -.1442903
       _cons |   40.60138   1.460454    27.80   0.000     37.70079    43.50197
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5) force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =     53.44
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0043696   .0006048    -7.23   0.000    -.0055709   -.0031683
      trend2 |  -.0025926   .0004254    -6.09   0.000    -.0034376   -.0017476
       _cons |   1.322283   .0081241   162.76   0.000     1.306145    1.338421
------------------------------------------------------------------------------

. replace trend1=year-1900;
(47 real changes made)

. replace trend2=year-1900;
(48 real changes made)

. replace trend2=0 if year<1924;
(53 real changes made)

. replace trend1=0 if year>1923;
(42 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     65.82
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1714409   .0680765    -2.52   0.014    -.3066467   -.0362351
      trend2 |  -.2117752   .0261844    -8.09   0.000    -.2637796   -.1597708
       _cons |   40.66177   1.174811    34.61   0.000      38.3285    42.99505
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5) force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =     64.94
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0044682    .000455    -9.82   0.000    -.0053719   -.0035645
      trend2 |  -.0025509    .000393    -6.49   0.000    -.0033316   -.0017703
       _cons |   1.323209   .0068558   193.01   0.000     1.309591    1.336828
------------------------------------------------------------------------------

. replace trend1=year-1900;
(42 real changes made)

. replace trend2=year-1900;
(53 real changes made)

. replace trend2=0 if year<1929;
(58 real changes made)

. replace trend1=0 if year>1928;
(37 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     67.22
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1732014   .0491959    -3.52   0.001    -.2709087    -.075494
      trend2 |  -.2120093   .0224034    -9.46   0.000    -.2565044   -.1675141
       _cons |   40.61032    1.01087    40.17   0.000     38.60265      42.618
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5) force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =     65.68
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0041794   .0004138   -10.10   0.000    -.0050014   -.0033573
      trend2 |  -.0026077   .0003957    -6.59   0.000    -.0033937   -.0018218
       _cons |   1.327188   .0067254   197.34   0.000     1.313829    1.340547
------------------------------------------------------------------------------

. replace trend1=year-1900;
(37 real changes made)

. replace trend2=year-1900;
(58 real changes made)

. replace trend2=0 if year<1934;
(63 real changes made)

. replace trend1=0 if year>1933;
(32 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     68.70
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1639827   .0382261    -4.29   0.000    -.2399029   -.0880624
      trend2 |  -.2167988   .0198209   -10.94   0.000    -.2561649   -.1774327
       _cons |   40.61464   .9336044    43.50   0.000     38.76042    42.46886
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5) force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =     70.67
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0040107   .0003716   -10.79   0.000    -.0047487   -.0032726
      trend2 |  -.0026104   .0003995    -6.53   0.000    -.0034039   -.0018168
       _cons |   1.329707   .0068323   194.62   0.000     1.316136    1.343279
------------------------------------------------------------------------------

. replace trend1=year-1900;
(32 real changes made)

. replace trend2=year-1900;
(63 real changes made)

. replace trend2=0 if year<1939;
(68 real changes made)

. replace trend1=0 if year>1938;
(27 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     77.52
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1588148   .0317178    -5.01   0.000     -.221809   -.0958205
      trend2 |   -.222585   .0180944   -12.30   0.000    -.2585221   -.1866479
       _cons |   40.58343   .9020005    44.99   0.000     38.79198    42.37488
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5)   force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =     89.63
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |    -.00397   .0003103   -12.80   0.000    -.0045863   -.0033537
      trend2 |  -.0025363   .0003945    -6.43   0.000    -.0033199   -.0017528
       _cons |   1.331177   .0067791   196.36   0.000     1.317711    1.344643
------------------------------------------------------------------------------

. replace trend1=year-1900;
(27 real changes made)

. replace trend2=year-1900;
(68 real changes made)

. replace trend2=0 if year<1944;
(73 real changes made)

. replace trend1=0 if year>1943;
(22 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     86.52
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |   -.165427   .0268219    -6.17   0.000    -.2186977   -.1121563
      trend2 |   -.225366   .0171948   -13.11   0.000    -.2595164   -.1912155
       _cons |   40.51649   .8818412    45.95   0.000     38.76508     42.2679
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5)  force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =    114.79
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |   -.003967   .0002667   -14.87   0.000    -.0044968   -.0034371
      trend2 |  -.0023854   .0003616    -6.60   0.000    -.0031037   -.0016671
       _cons |   1.332364   .0067739   196.69   0.000     1.318909     1.34582
------------------------------------------------------------------------------

. replace trend1=year-1900;
(22 real changes made)

. replace trend2=year-1900;
(73 real changes made)

. replace trend2=0 if year<1949;
(78 real changes made)

. replace trend1=0 if year>1948;
(17 real changes made)

. newey mec trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        95
maximum lag: 5                                      F(  2,    92)  =     96.05
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
         mec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.1814677   .0248857    -7.29   0.000    -.2308928   -.1320426
      trend2 |  -.2215281   .0161244   -13.74   0.000    -.2535526   -.1895035
       _cons |   40.45735   .8614208    46.97   0.000     38.74649     42.1682
------------------------------------------------------------------------------

.  newey wage trend1 trend2, lag(5) force;

Regression with Newey-West standard errors          Number of obs  =        94
maximum lag: 5                                      F(  2,    91)  =    133.48
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
        wage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |   -.003905   .0002442   -15.99   0.000    -.0043901   -.0034199
      trend2 |  -.0021733   .0003191    -6.81   0.000    -.0028072   -.0015395
       _cons |     1.3336   .0068212   195.51   0.000      1.32005    1.347149
------------------------------------------------------------------------------

. /* Ireland Wages */
> 
> use "irelandwagesrep.dta", clear;

. tsset year;
        time variable:  year, 1926 to 1984
                delta:  1 unit

. gen trend1=year-1900;

. gen trend2=year-1900;

. replace trend1=year-1900;
(0 real changes made)

. replace trend2=year-1900;
(0 real changes made)

. replace trend2=0 if year<1931;
(5 real changes made)

. replace trend1=0 if year>1930;
(54 real changes made)

. newey ratio trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     62.25
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0049123   .0009955    -4.93   0.000    -.0069065   -.0029182
      trend2 |  -.0039662   .0005138    -7.72   0.000    -.0049956   -.0029369
       _cons |   1.449942   .0278963    51.98   0.000     1.394059    1.505825
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(54 real changes made)

. replace trend2=year-1900;
(5 real changes made)

. replace trend2=0 if year<1936;
(10 real changes made)

. replace trend1=0 if year>1935;
(49 real changes made)

. newey ratio trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     49.42
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0047416    .001182    -4.01   0.000    -.0071095   -.0023738
      trend2 |  -.0040545   .0006303    -6.43   0.000    -.0053172   -.0027918
       _cons |   1.456106   .0368578    39.51   0.000     1.382271    1.529941
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(49 real changes made)

. replace trend2=year-1900;
(10 real changes made)

. replace trend2=0 if year<1941;
(15 real changes made)

. replace trend1=0 if year>1940;
(44 real changes made)

. newey ratio trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     43.26
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0036084   .0015598    -2.31   0.024    -.0067331   -.0004836
      trend2 |  -.0037006   .0007889    -4.69   0.000     -.005281   -.0021202
       _cons |   1.432313   .0511314    28.01   0.000     1.329884    1.534741
------------------------------------------------------------------------------

.  replace trend1=year-1900;
(44 real changes made)

. replace trend2=year-1900;
(15 real changes made)

. replace trend2=0 if year<1946;
(20 real changes made)

. replace trend1=0 if year>1945;
(39 real changes made)

. newey ratio trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     56.20
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0026217   .0014529    -1.80   0.077    -.0055322    .0002888
      trend2 |  -.0032634   .0007963    -4.10   0.000    -.0048586   -.0016683
       _cons |   1.401321    .054085    25.91   0.000     1.292975    1.509666
------------------------------------------------------------------------------

. test trend1=trend2;

 ( 1)  trend1 - trend2 = 0

       F(  1,    56) =    0.84
            Prob > F =    0.3632

. replace trend1=year-1900;
(39 real changes made)

. replace trend2=year-1900;
(20 real changes made)

. replace trend2=0 if year<1951;
(25 real changes made)

. replace trend1=0 if year>1950;
(34 real changes made)

. newey ratio trend1 trend2, lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     78.92
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0007566   .0009073    -0.83   0.408    -.0025741    .0010609
      trend2 |  -.0023633   .0005442    -4.34   0.000    -.0034535   -.0012731
       _cons |   1.333665   .0353558    37.72   0.000     1.262839    1.404491
------------------------------------------------------------------------------

. replace trend1=year-1900;
(34 real changes made)

. replace trend2=year-1900;
(25 real changes made)

. replace trend2=0 if year<1956;
(30 real changes made)

. replace trend1=0 if year>1955;
(29 real changes made)

. newey ratio trend1 trend2 , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     56.31
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0012342   .0008517    -1.45   0.153    -.0029404     .000472
      trend2 |  -.0025636   .0005201    -4.93   0.000    -.0036056   -.0015216
       _cons |   1.343176   .0328212    40.92   0.000     1.277427    1.408924
------------------------------------------------------------------------------

. replace trend1=year-1900;
(29 real changes made)

. replace trend2=year-1900;
(30 real changes made)

. replace trend2=0 if year<1961;
(35 real changes made)

. replace trend1=0 if year>1960;
(24 real changes made)

. newey ratio trend1 trend2  , lag(5);

Regression with Newey-West standard errors          Number of obs  =        59
maximum lag: 5                                      F(  2,    56)  =     37.86
                                                    Prob > F       =    0.0000

------------------------------------------------------------------------------
             |             Newey-West
       ratio |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      trend1 |  -.0035238   .0009593    -3.67   0.001    -.0054454   -.0016021
      trend2 |  -.0036505   .0005809    -6.28   0.000    -.0048141   -.0024869
       _cons |   1.427099   .0359429    39.70   0.000     1.355097    1.499101
------------------------------------------------------------------------------

. clear;

. /**********************
> Descriptive Statistics of Data for Main Analyses (Appendix Table 3)
> **********************/
> 
> misum iqimpr wcentld wdeccentld fempart mgdppc leftgov nondem secsharel10 top
> 1la top10la top10la_top1la
> tradedep totden2 funisuf wagctl2 if 
> (period>3 & stnum~=205) | (period>5 & stnum==205), nsets(10);
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )
(Written by R.              )

Multiple Imputation Mean Estimates

--------------------------------------------------
Variable |     Obs        Mean    Std Err of Mean
--------------------------------------------------
 wcentld |     219    .1415525         .0230711
wdeccentld |     219  .4374429         .0330704
 fempart |     219    .3093035         .0099562
  mgdppc |     219    9.475359         .3873564
 leftgov |     219    .3896934         .0269866
  nondem |     219    .0922374         .0187235
secsharel10 |     219 .3861581         .0190197
  top1la |     219    10.72191         .2578905
 top10la |     219    34.88008         .3730821
top10la_top1la |     219 27.16771      .2580699
tradedep |     219    40.11525          1.62357
 totden2 |     219    34.62969         1.070337
 funisuf |     219    .7680365         .0281144
 wagctl2 |     219     1.70411         .0465532
--------------------------------------------------


. log close;
       log:  C:\wip\inequality\replicationdata2\SSreplication.log
  log type:  text
 closed on:   4 Oct 2008, 16:28:22
-------------------------------------------------------------------------------
